A known problem in the field of sensing is cross-sensitivity of a sensor, that is, the sensor's undesirable responses to interferences such as compounds other than an analyte to be detected, or physical environmental factors including but not limited to temperature, humidity, and pressure. Cross-sensitivity of the sensor is particularly problematic when the analyte to be detected is at a very low concentration such as a trace level, and a strong response of the sensor to interferences masks the response of the sensor to the analyte. For example, a high level sensor response to humidity may interfere with a response of the sensor built to detect a trace level of explosives.
The problem of cross-sensitivity is typically addressed by arranging a plurality of sensors into a sensor array and processing the array responses using multivariate analysis. In the sensor array, individual sensors are coated with different sensing materials and one response per sensing material (e.g., resistance, current, capacitance, work function, mass, optical thickness, light intensity) is measured. However, the sensor array approach increases numbers of sensors used, and introduces complexity of sensing material deposition and device fabrication.
Using a sensor array instead of a single sensor allows sensor responses to be corrected for interferences such as humidity and typically works over a short period of time. However, independent drift of each sensor in the sensor array may occur over long term, making it necessary to perform frequent calibrations of sensors, which are often labor intensive and time consuming.
The independent drift of each sensor in the sensor array is a result of using different sensing material for each sensor in an array. Each sensor would have its own drift and degradation profile, uncorrelated with the profiles of other sensors. This uncorrelated drift of each sensor leads to significant challenges in keeping sensor arrays within their original specifications.
Another known challenge in sensing is detection of non-volatile compounds in an environment, such as particulates of different natures. Non-limiting examples of such particulates include inorganic particles such as oxidizer salts, organic particles such as explosives, and biological particles such as viruses and spores. At present, detection of particles in an environment (for example, air) often requires complicated equipment including, for example, a pump for air sampling, a set of filters, baffles, or other engineered structures to separate only particles of interest from the rest of collected debris, and a detector to analyze the particles of interest.
Therefore, there is an ongoing need for an improved system and method for sensing volatile and non-volatile analytes in an environment by using a single sensor having high analyte selectivity, low response to interferences, and minimized needs for frequent calibrations. In addition, there is a continuing need for rapid sensing techniques especially for certain sensing applications including but not limited to security applications, for example, detection of explosives in airports and the like.